Journal ArticleDOI
Applications of Computer-Intensive Statistical Methods to Environmental Research
TLDR
Application to a real data set illustrates the advantages of distribution-free statistical methods, including freedom from distribution assumptions without loss of power, complete choice over test statistics, easy adaptation to design complexities and missing data, and considerable intuitive appeal.About:
This article is published in Ecotoxicology and Environmental Safety.The article was published on 1998-02-01. It has received 24 citations till now. The article focuses on the topics: Sampling distribution & Resampling.read more
Citations
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The bootstrap: A technique for data-driven statistics. Using computer-intensive analyses to explore experimental data
TL;DR: These techniques can supplement current nonparametric statistical methods and should be included, where appropriate, in the armamentarium of data processing methodologies.
Journal ArticleDOI
A general best-fit method for concentration-response curves and the estimation of low-effect concentrations
Martin Scholze,Wolfgang Boedeker,Michael Faust,Thomas Backhaus,Rolf Altenburger,L. Horst Grimme +5 more
TL;DR: The best-fit method for the estimation of low-effect concentrations is validated by a simulation study, and its applicability is demonstrated with toxicity data for 64 chemicals tested in an algal and a bacterial bioassay, where a clear improvement is achieved.
Journal ArticleDOI
Discriminant function analysis with nonindependent data : consequences and an alternative
Roger Mundry,Christina Sommer +1 more
TL;DR: In this article, the authors show that analyzing factorial data sets using a conventional discriminant function analysis is a case of pseudoreplication and tends to produce (sometimes grossly) incorrect results.
Journal ArticleDOI
Fine sediment deposition in streams after selective forest harvesting without riparian buffers
TL;DR: Fine sediment accumulation was measured in streams in low-order forest watersheds across a gradient of selective harvesting with no protective riparian buffers.
References
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Journal ArticleDOI
Statistical Principles in Experimental Design
TL;DR: This chapter discusses design and analysis of single-Factor Experiments: Completely Randomized Design and Factorial Experiments in which Some of the Interactions are Confounded.
Biometery: The principles and practice of statistics in biological research
TL;DR: In this paper, the authors present a model for the analysis of variance in a single-classification and two-way and multiway analysis of Variance with the assumption of correlation.
Book
Biometry: The Principles and Practice of Statistics in Biological Research
Robert R. Sokal,F. James Rohlf +1 more
TL;DR: In this paper, the authors present a model for the analysis of variance in a single-classification and two-way and multiway analysis of Variance with the assumption of correlation.
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